Sources of anthropometric data, specifically body segment inertial parameters, are of critical importance in ergonomics and occupational biomechanics. Current models predicting such anthropometric variables are developed based on data collected in normal-weight young adults. Yet, over 60% of all US workers are either overweight or obese and this obesity epidemic worsens with increasing age with more than 75% of workers over the age of 60 years old being overweight or obese. Thus, there is a need to generate new models to predict body segment parameters that better reflect the working population. We propose to develop new datasets of body segment parameters that include body mass index (BMI) as a factor across the age span of working adults using Dual Energy X-Ray Absorption (DXA) methods. More specifically, the goal of the proposed project is two-fold: (1) quantify the impact of obesity on body segment parameters in full-time workers aged 21 to 70 years old (Aim #1), and (2) develop BMI-specific regression models for the prediction of body segment parameters in the same population (Aim #2). To achieve these aims, full-time workers between the ages of 21 and 70 years old will be recruited for participation in the proposed project. They will be asked to come in for one visit. During this visit, a whole-body DXA scan will be collected to derive in-vivo measures of body segment parameters. Body measurements will also be collected. Standard multivariate regression models will be used to achieve the aims of the proposed project. In summary, with the aging of the US workforce and prevalence rates of obesity and overweight in this population, it is critical that we develop validated models that accurately predict body segment parameters in working adults, taking into account body mass and age. The proposed project will address this gap in the ergonomics and occupational biomechanics literature.